Software development

Software development

Giving coding agents full access to all of Ramp's engineering tools is what makes Inspect truly innovative. Instead of only letting agents write basic code, Ramp's system runs in sandboxed virtual machines on Modal. It works seamlessly with databases, CI/CD pipelines, monitoring tools like Sentry and Datadog, feature flags, and communication platforms such as Slack and GitHub. Agents can write code and ensure it works by using the same testing and validation processes that engineers use every day.

Just as software finished eating the world, zero interest rates ended. Companies optimized for cash and slowed hiring. The market didn't shrink, but stopped growing at the breakneck pace we all expected. The result: a glut of entry level talent groomed for jobs that never materialized. This would explain a more competitive entry level market. But it doesn't explain the entry-level market shrinking, despite overall industry growth. In short: demand for senior talent is rising, but has fallen off a cliff for juniors.

After some investigation, I found that Home Assistant has an integration with Node-RED - a graphical tool for manipulating data and event streams. It could probably satisfy most of my needs. But from time to time I remember that I'm a professional software developer, working with event streams for many years, and for this kind of problem there's nothing better than math (and Scala's type system, which supports it very well).

"That's how people create flash USDT BEP-20 using Remix and MetaMask" is a tutorial video claiming to show how to create a USDT-like BEP-20 token on the BNB Smart Chain using Remix (a smart contract IDE) and MetaMask (a crypto wallet). It walks through writing and deploying a smart contract that purportedly generates a custom token called flash USDT, demonstrating the process of compiling, deploying, and interacting with the contract in MetaMaskhttps://youtu.be/HlptFM3zbTQ?si=iy9u8PYBGBPM2zZs https://youtu.be/HlptFM3zbTQ?si=Dw2pPzdGd3RUAIiX

The "What's New" first-run experience will appear during startup to guide users through the app's latest features. According to Microsoft, "this dialog provides a quick overview of what's possible in Notepad and serves as a helpful starting point for both new and returning users." It can be closed and reopened by clicking a megaphone icon in the top-right of the toolbar.

Central to the GA release is Agentic Chat. This functionality builds on the previously introduced Duo Chat but goes a step further by leveraging context from virtually every part of GitLab. Think of issues, merge requests, CI/CD pipelines, and security findings. Agentic Chat can not only advise, but also actually perform actions on behalf of developers, depending on the rights and approvals that have been set.

Manjaro is a sweet Arch-based Linux distribution, and it has the fans to prove it. Manjaro is designed to take Arch to new heights of user-friendliness, and it succeeds quite well. Of course, there are always those who believe everything can be improved, which is why a small team of developers decided to fork Manjaro and create Elegance. The beauty of Elegance isn't in the UI, although the developers have made Cinnamon look pretty good.

There is no flow state that comes from building a Mac app using AI with Claude Code. If you've ever managed programmers, you know what using Claude Code feels like. It is an enormous force multiplier, but you're going to spend most of your time cajoling and correcting, and some of your time trying to chart your way out of AI-generated chaos.

The COVID-19 pandemic has emptied the world's offices, sending most of us to work from home for the foreseeable future and facilitating a mass migration to the digital workplace. But will it also jumpstart the arrival of our non-human colleagues? AMELIA ("AI + ME = AMELIA") from IPsoft can read 300 pages in 30 seconds, comprehend multiple languages (including logic and context), and is installed in more than 500 banks, insurance companies, and retail giants.

When I work on something, whether it's at Interfere or my personal projects, I like to experiment a lot. Design engineering is a lot about trial and error, and I often spend hours trying to find the "this feels right" moment. This is where AI helps. Instead of spending hours on a concept that I'm unsure of, I try that concept out in a matter of minutes, and throw it away if it doesn't feel right.

Key Issues: General UI Lag: Clicking between slides or menus is delayed and often "hangs." Audio/Text Desync: When adjusting text boxes to narration, the audio continues to play but the UI/subtitles freeze for several seconds. Overall Stability: The app feels unresponsive and struggles to handle the project size. What can I do to resolve this issue?Because currently the app is unusable for professional production.

A trade-free operating system, that's what Tromjaro means. But what does a trade-free operating system have to offer? Well, it means a lot, especially if you're tired of the imbalance between those who have versus those who want. From the developers' perspective, this "trade-free" OS wants nothing from its users, such as no data collection and no demands for attention: "This is the purest form of free and the most honest one."

I'll be talking about holistic engineering or the practice of factoring in your technical decisions, designs, strategies, all the non-technical factors that are actually forces that influence your organic socio-technical problem space. As much as you can see in this canyon how natural forces have influenced the shape of the earth, so you can see the color. You can see all the different layers.

A little bit about myself. In my previous life, I was staff platform engineering. I focused a lot of development engineering and everything that basically was the sociotechnical aspect of our technical work. I recently was working as a CTO and co-founder of a startup, and nowadays I'm just doing advisory roles and a little bit of consulting while trying to think about the next big thing. Yes, so happy to be talking with you, Shane.

It was almost certainly time for a change,

Software engineering didn't adopt AI agents faster because engineers are more adventurous, or the use case was better. They adopted them more quickly because they already had Git. Long before AI arrived, software development had normalized version control, branching, structured approvals, reproducibility, and diff-based accountability. These weren't conveniences. They were the infrastructure that made collaboration possible. When AI agents appeared, they fit naturally into a discipline that already knew how to absorb change without losing control.

Over the past decade, software development has been shaped by two closely related transformations. One is the rise of devops and continuous integration and continuous delivery (CI/CD), which brought development and operations teams together around automated, incremental software delivery. The other is the shift from monolithic applications to distributed, cloud-native systems built from microservices and containers, typically managed by orchestration platforms such as Kubernetes.

In total I probably spent around 45 minutes actively with it. It worked for around 3 hours while I was watching, then another 7 hours alone. This post is a recollection of what happened and what I learned from it. All prompting was done by voice using pi, starting with Opus 4.5 and switching to GPT-5.2 Codex for the long tail of test fixing.

When I joined Google ~14 years ago, I thought the job was about writing great code. I was partly right. But the longer I've stayed, the more I've realized that the engineers who thrive aren't necessarily the best programmers - they're the ones who've figured out how to navigate everything around the code: the people, the politics, the alignment, the ambiguity.

A recent commit to integrate and enable the JXL decoder means that future releases of Google Chrome and other Chromium-based browsers will include code to process and present JXL images. The format's supporters argue JXL can be used to recompress existing JPEG images without loss so they're 20 percent smaller, which alone would represent a significant bandwidth saving for websites and content delivery networks.